The present invention relates to systems for delivery of energy resources, and, more particularly, to systems for controlling the distribution of energy for example in the form of electricity and/or heat, such as within a local network or grid.
There exist a number of examples of local energy networks, or micro-grids, across which energy resources are to be distributed, such as: a plurality of connected or co-located commercial, industrial or domestic premises; different departments or functions within commercial or industrial premises; and, different systems aboard vehicles, such as aircraft, trains, ships, etc. Each of the different components of such local networks have individual energy/heating requirements, which can fluctuate over time.
In the case of different premises, each of the premises may individually draw all electrical power or gas from a mains supply. Similarly vehicles may be temporarily connected to external power supplies. In examples of local networks, which additionally or alternatively have local power generation facilities, there is a more complex problem of how best to distribute energy between the different components of the local network. A balance is generally required to be struck between satisfying all of the essential local network energy demands and achieving the best possible energy efficiency over the local network.
There are multiple problems encountered when attempting to determine an energy efficient time-varying distribution of electrical and heating load over a number of generators and boilers within a geographically limited area, including: satisfying local energy/heat demands; constraints introduced by the limited transportability of heat; the varying efficiencies of different types of generators as well as the varying efficiencies of each generator at different loading-levels; and, efficiency losses incurred by the need to draw energy from the wider electrical grid, potentially including the highly time-varying cost of electricity bought from or sold to the wider grid.
It is known within the art to perform a centralised calculation of the “optimum” distribution of heating and electrical generation load for some future time period, given a forecast of user demands during that same period. The centralised calculation is then followed by the issuing of instructions and the attempted implementation of the determined optimum distribution when the relevant time period arrives. This approach can be summarised as “calculate, then deploy” strategy, which has a number of drawbacks within the context of the resource allocation problem set out above. These drawbacks arise principally from a lack of continuous adaptability, and the need to recalculate an optimal distribution in its entirety when circumstances change.
In particular, real, current energy demands can differ from those assumed during the advance calculations. This could be due to imperfect forecasting or changes in requirements between the calculation and deployment. The consequences of this mean that adjustments to the determined solution will frequently be necessary in order to ensure that demand is met. Furthermore the resources available to satisfy energy demands typically change over time. Reasons for this may include boiler or generator breakdown, grid power cut, fuel delivery failure, planned or unplanned maintenance etc. This may require significant changes, at short notice, to be made to the determined solution.
An additional drawback of the prior art is the difficulty in achieving dynamic demand-side management in response to changing resource availability or price signals.
It is an aim of the present invention to provide an improved energy distribution system, which overcomes or at least partially mitigates one or more of the above problems. It may be considered an additional or alternative aim to provide an improved system for managing energy delivery over a local energy network or micro-grid.